The decennial Census of India is the largest single administrative exercise
of its kind in the World. Even the preparations for it make news because
of the size and impact of the operation. The Census operations as well
as the data thrown up by it can be the source of many news stories and
features for the journalist. From the last Census, held in 1991, the data
collected have been computerised. This time, it is expected to be done
in a more systematic way. This discussion, towards its end, will give you
some idea of how this data would be structured and what the reporter can
look for in them.

This time, the Census would be enumerating the disabled people in the
country. This would be the first time that such authentic figures on disability
become available. This could yield stories relating to the number and
percentage of disabled in the country, especially in relation to the reservation
of jobs available.

The male to female ratio is one of the items always watched by demographers
and journalists. Normally, women should slightly outnumber men. If this
is not so in the States and districts, it indicates that the status of
women is not good in that region. The sex ratio (number of females per 1000 males) and life
expectancy of women in Kerala may be higher than even that of Washington D.
C. (USA). Several items of Census data such as the decadinal population
growth and literacy rate could be of special interest to journalists
as they may point to success or failure of the family planning, literacy and other programmes.
As India had regular census from 1881 onwards, comparing the population
data with that of the last century would yield interesting insights.

The Census is being conducted in two phases. The first phase consisting
of house listing operations is already complete. When compiled, this would
draw up information on housing conditions, availability of the basic amenities
such as electricity, drinking water, toilet and bath rooms, ownership of
houses and possession of vehicles. Much of these are new information which
were not collected before.

The second phase covers canvassing of details such as general and socio-cultural
characteristics (these include religion, mother tongue, languages known,
literacy and educational status), characteristics of workers and non-workers,
migration characteristics and fertility particulars.

For the first time, the following information will be canvassed.

Age of marriage
Disabilities
Languages known
Distance traveled to place of work and mode of travel.
Migration after birth
Level of Education and type of institution attended.

Two digits (within the country)
Two digits (within the State/UT)
Four digits (within the district)
Eight digits (within the State/ UT)
Eight digits (within the district)
Four digits (within the town)

Data is separately compiled for rural and urban areas. For Census purposes,
besides the statutory towns such as municipalities, city corporations
and town panchayats, some villages that satisfy a three fold criteria
(population, density and male non-agricultural workers) are considered
as Census town. The rest area treated as rural.

The data collected in the Census is published by the Census Commissioner
of India as Census
Series and Tables. Many of these are now available in the electronic
form. The State Directorates publish State-wise
data. The data both in print and electronic form can usually be obtained
free of charge by media organizations from the Census offices.

Data Structure:

In 1991, the data was made available as several database (.DBF) files.
(They can be obtained from the Census Directorates/National Informatics
Centre). These used a 16 digit location code (eg. 1400303001010002) for
urban data and 18 digit code for rural (eg. 140030003000300005) data at
the State level. The first two digits represented the district. For example,
the code for Kasaragod district was 01 and that for Thiruvananthapuram
was 14. The next four digits represented the taluk/tahsil in case
of urban areas. In case of rural areas, six digits were used to represent
the development blocks. The next six digits stood for the town/village
panchayat. The last four digits were for representing the wards.

In the 2001 Census, the coding is slightly different from 1991.
The State/Union Territory is represented by two digits each in the
code. In the State level data, the first two digits denote the
district.
The next four represent taluk, tahsil, P. S., development block,
circle or mandal as is relevant to each State. The towns as well as the
villages are represented separately through Permanent Location Code
Numbers consisting of eight digits for villages and four for wards.
Beginning
with the first village of the first district to the last village in the
last district, there is a continuous running number code for each
village. The eight digits provided to represent the village will help
addition
of new villages in future without disturbing the overall scheme.

To see the organisation of data, let us take the example of two files
representing the code and data relating to industrial categories of workers
and non-workers for urban areas. The first will contain records with the
code and the corresponding name of taluk, town and ward. The other file
will contain records with the location code along with fields having the
actual population data. The starting point in using these files is to set
a relationship between the two files using the code. When the codes are
matched, we know which data represent which village.

The data can be processed by reporters having some knowledge in using
database programs. Some manipulations would require programing skills.
This raw data can throw up a lot of information and story leads if
you look at it closely. A high incidence a disability in a village may
merit a field level investigation. If a high male female ratio is noticed
in some villages compared to the neighbouring villages, it could be the
place do an investigation about the condition of women, possible prevalence
of female infanticide etc. How does the districts/villages compare in literacy,
fertility, population growth etc could yield human interest stories.One
can even find out which ward in one's city is having the highest number
of cars. Which town poses the biggest problem for the office goers in terms
of distance to be travailed to reach the office? The story possibilities
are numerous.